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Welcome to the DCPS Lab

The Dependable Cyber-Physical Systems (DCPS) lab is directed by Prof. Khaza Anuarul Hoque and located in the F. Robert & Patricia Naka Hall building at University of Missouri-Columbia. The research mission of the DCPS Laboratory is to develop theory, methods, and tools for supporting modeling, design, and (formal) verification of highly dependable embedded and cyber-physical systems (CPS). Specifically, the goal of DCPS lab is to enhance the reliability, safety, security and energy efficiency of complex computing systems.

To this end, we conduct interdisciplinary research to answer the scientific questions we deem most important, specifically in the following areas (see Research).

  • Formal method in robotics and automation.
  • Fault tolerant, secure and energy-efficient ML/AI hardware.
  • Cybersecurity issues in virtual reality (VR) applications.
  • Cybersecurity issues in intelligent prognostics.

We are grateful for funding from National Science Foundation (NSF), United States Naval Research Laboratory (NRL), and University of Missouri.


January 2023

Our paper titled ‘Exposing Reliability Degradation and Mitigation in Approximate DNNs under Permanent Faults’ has been accepted for publication in the IEEE Transactions on Very Large Scale Integration (VLSI) Systems Journal (IF 2.775).
See Preprint.

January 2023

Our paper titled ‘VR-LENS: Super Learning-based Cybersickness Detection and Explainable AI-Guided Deployment in Virtual Reality’ has been accepted for publication in the annual ACM Conference on Intelligent User Interfaces (AM IUI) conference (core rank A).
Preprint will be available soon.

December 2022

Our paper titled ‘LiteVR: Interpretable and Lightweight Cybersickness Detection using Explainable AI’ has been accepted for publication in the IEEE Virtual Reality (IEEE VR) conference (core rank A*).
Preprint will be available soon.

November 2022

Two papers from our lab have been accepted in the Design, Automation and Test in Europe (DATE 2023) Conference titled ‘Improving Reliability of Spiking Neural Networks through Fault Aware Threshold Voltage Optimization’ and ‘Security-Aware Approximate Spiking Neural Network’ with an acceptance rate of 25%.
See Preprint 1, Preprint 2, MU news.

October 2022

Our paper titled ‘Detection of Security and Privacy Attacks Disrupting User Immersive Experience in Virtual Reality Learning Environments’ has been accepted for publication in the IEEE Transactions on Services Computing (IEEE TSC) Journal (IF 11.02).
See Preprint.

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